SEMANTIC REPRESENTATION MODULE OF A MACHINE-LEARNING ENGINE IN A VIDEO ANALYSIS SYSTEM
First Claim
1. A method for processing data describing a scene depicted in a sequence of video frames, the method comprising:
- receiving input data describing one or more objects detected in the scene, wherein the input data includes at least a classification for each of the one or more objects;
identifying one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by at least one of the objects depicted in the sequence of video frames and wherein each primitive event has an assigned primitive event symbol;
generating, for one or more objects, a primitive event symbol stream which includes the primitive event symbols corresponding to the primitive events identified for a respective object;
generating, for one or more objects, a phase space symbol stream, wherein the phase space symbol stream describes a trajectory for a respective object through a phase space domain;
combining the primitive event symbol stream and the phase space symbol stream for each respective object to form a first vector representation of that object; and
passing the first vector representations to a machine learning engine configured to identify patterns of behavior for each object classification from the first vector representation.
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Abstract
A machine-learning engine is disclosed that is configured to recognize and learn behaviors, as well as to identify and distinguish between normal and abnormal behavior within a scene, by analyzing movements and/or activities (or absence of such) over time. The machine-learning engine may be configured to evaluate a sequence of primitive events and associated kinematic data generated for an object depicted in a sequence of video frames and a related vector representation. The vector representation is generated from a primitive event symbol stream and a phase space symbol stream, and the streams describe actions of the objects depicted in the sequence of video frames.
162 Citations
21 Claims
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1. A method for processing data describing a scene depicted in a sequence of video frames, the method comprising:
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receiving input data describing one or more objects detected in the scene, wherein the input data includes at least a classification for each of the one or more objects; identifying one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by at least one of the objects depicted in the sequence of video frames and wherein each primitive event has an assigned primitive event symbol; generating, for one or more objects, a primitive event symbol stream which includes the primitive event symbols corresponding to the primitive events identified for a respective object; generating, for one or more objects, a phase space symbol stream, wherein the phase space symbol stream describes a trajectory for a respective object through a phase space domain; combining the primitive event symbol stream and the phase space symbol stream for each respective object to form a first vector representation of that object; and passing the first vector representations to a machine learning engine configured to identify patterns of behavior for each object classification from the first vector representation. - View Dependent Claims (2, 3, 4, 5, 6, 7)
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8. A computer-readable storage medium containing a program, which, when executed on a processor is configured to perform an operation for processing data describing a scene depicted in a sequence of video frames, comprising:
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receiving input data describing one or more objects detected in the scene, wherein the input data includes at least a classification for each of the one or more objects; identifying one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by at least one of the objects depicted in the sequence of video frames and wherein each primitive event has an assigned primitive event symbol; generating, for one or more objects, a primitive event symbol stream which includes the primitive event symbols corresponding to the primitive events identified for a respective object; generating, for one or more objects, a phase space symbol stream, wherein the phase space symbol stream describes a trajectory for a respective object through a phase space domain; combining the primitive event symbol stream and the phase space symbol stream for each respective object to form a first vector representation of that object; and passing the first vector representations to a machine learning engine configured to identify patterns of behavior for each object classification from the first vector representation.
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- 9. The computer-readable storage medium of claim 9, wherein the operation further comprises, applying a singular value decomposition (SVD) to the first vector representations to generate a second vector representation from each first vector representation, wherein the second vector representations reduce the dimensionality of the corresponding first vector representation.
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15. A system, comprising:
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a video input source; a processor; and a memory storing a machine learning engine, wherein the machine learning engine is configured to; receive input data describing one or more objects detected in the scene, wherein the input data includes at least a classification for each of the one or more objects; identifying one or more primitive events, wherein each primitive event provides a semantic value describing a behavior engaged in by at least one of the objects depicted in the sequence of video frames and wherein each primitive event has an assigned primitive event symbol; generate, for one or more objects, a primitive event symbol stream which includes the primitive event symbols corresponding to the primitive events identified for a respective object; generate, for one or more objects, a phase space symbol stream, wherein the phase space symbol stream describes a trajectory for a respective object through a phase space domain; combine the primitive event symbol stream and the phase space symbol stream for each respective object to form a first vector representation of that object; and pass the first vector representations to a machine learning engine configured to identify patterns of behavior for each object classification from the first vector representation. - View Dependent Claims (16, 17, 18, 19, 20, 21)
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Specification